Production technology and agglomeration for Japanese prefectures during 1991-2000

Abstract

We analyse the seemingly unrelated regression (SUR) models with spatial dependencies from a Bayesian point of view and estimate the parameters of the models using a Markov chain Monte Carlo (MCMC) method. Further, we analyse the production technology and the economics of agglomeration in Japanese prefectures from 1991 to 2000, simultaneously taking into account spatial and serial correlation. Model comparison is done via log-marginal likelihoods, and it is found that the spatial error SUR model is the best model and that the economics of agglomeration and spatial heterogeneity decreased over this decade. © 2011 the author(s). Papers in Regional Science © 2011 RSAI.